Searching Trajectories by Regions of Interest

Shuo Shang, Lisi Chen, Christian Søndergaard Jensen, Ji-Rong Wen, Panos Kalnis

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

Resumé

We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in applications such as trip planning and recommendation. To process the TSR query, a set of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.
OriginalsprogEngelsk
TitelProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
Antal sider2
Publikationsdato24 okt. 2018
Sider1741-1742
Artikelnummer8509449
ISBN (Trykt)978-1-5386-5520-7
ISBN (Elektronisk)9781538655207
DOI
StatusUdgivet - 24 okt. 2018
Begivenhed34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, Frankrig
Varighed: 16 apr. 201819 apr. 2018

Konference

Konference34th IEEE International Conference on Data Engineering, ICDE 2018
LandFrankrig
ByParis
Periode16/04/201819/04/2018

Fingerprint

Trajectories
Query processing
Planning
Experiments

Citer dette

Shang, S., Chen, L., Jensen, C. S., Wen, J-R., & Kalnis, P. (2018). Searching Trajectories by Regions of Interest. I Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018 (s. 1741-1742). [8509449] https://doi.org/10.1109/ICDE.2018.00228
Shang, Shuo ; Chen, Lisi ; Jensen, Christian Søndergaard ; Wen, Ji-Rong ; Kalnis, Panos. / Searching Trajectories by Regions of Interest. Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018. 2018. s. 1741-1742
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title = "Searching Trajectories by Regions of Interest",
abstract = "We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in applications such as trip planning and recommendation. To process the TSR query, a set of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.",
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author = "Shuo Shang and Lisi Chen and Jensen, {Christian S{\o}ndergaard} and Ji-Rong Wen and Panos Kalnis",
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Shang, S, Chen, L, Jensen, CS, Wen, J-R & Kalnis, P 2018, Searching Trajectories by Regions of Interest. i Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018., 8509449, s. 1741-1742, 34th IEEE International Conference on Data Engineering, ICDE 2018, Paris, Frankrig, 16/04/2018. https://doi.org/10.1109/ICDE.2018.00228

Searching Trajectories by Regions of Interest. / Shang, Shuo ; Chen, Lisi; Jensen, Christian Søndergaard; Wen, Ji-Rong; Kalnis, Panos.

Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018. 2018. s. 1741-1742 8509449.

Publikation: Bidrag til bog/antologi/rapport/konference proceedingKonferenceartikel i proceedingForskningpeer review

TY - GEN

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AU - Shang, Shuo

AU - Chen, Lisi

AU - Jensen, Christian Søndergaard

AU - Wen, Ji-Rong

AU - Kalnis, Panos

PY - 2018/10/24

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N2 - We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in applications such as trip planning and recommendation. To process the TSR query, a set of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.

AB - We propose and investigate a novel query type named trajectory search by regions of interest (TSR query). Given an argument set of trajectories, a TSR query takes a set of regions of interest as a parameter and returns the trajectory in the argument set with the highest spatial-density correlation to the query regions. This type of query is useful in applications such as trip planning and recommendation. To process the TSR query, a set of new metrics are defined to model spatial-density correlations. An efficient trajectory search algorithm is developed that exploits upper and lower bounds to prune the search space and that adopts a query-source selection strategy, as well as integrates a heuristic search strategy based on priority ranking to schedule multiple query sources. The performance of TSR query processing is studied in extensive experiments based on real and synthetic spatial data.

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KW - Spatial density correlation

KW - Spatial networks

KW - Trajectory search by regions

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Shang S, Chen L, Jensen CS, Wen J-R, Kalnis P. Searching Trajectories by Regions of Interest. I Proceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018. 2018. s. 1741-1742. 8509449 https://doi.org/10.1109/ICDE.2018.00228